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Modeling, simulation, and prediction of global energy indices: a differential approach

Frontiers in Energy 2022年第2期16卷 375-392页

作者： Stephen Ndubuisi NNAMCHI Onyinyechi Adanma NNAMCHI Janice Desire BUSINGYE maxwell azubuike ijomah Philip Ikechi OBASI Department of Mechanical Engineering Kampala International University20000 KampalaUganda Department of Agricultural Engineering and Bio Resources Michael Okpara University of AgricultureUmudikeUmuahiaNigeria Directorate of Human Resource/Finance Kampala International University20000 KampalaUganda Department of Mathematics and Statistics Faculty of SciencesUniversity of Port HarcourtPMB 5323 Choba Port HarcourtNigeria Department of Macroeconomic Analysis(Ministry of Finance) Budget and National PlanningAbujaNigeria

Modeling, simulation, and prediction of global energy indices remain veritable tools for econometric, engineering, analysis, and prediction of energy indices. Thus, this paper differentially modeled, simulated, and non-differentially predicated the global energy indices. The state-of-the-art of the research includes normalization of energy indices, generation of differential rate terms, and regression of rate terms against energy indices to generate coefficients and unexplained terms. On imposition of initial conditions, the solution to the system of linear differential equations was realized in a Matlab environment. There was a strong agreement between the simulated and the field data. The exact solutions are ideal for interpolative prediction of historic data. Furthermore, the simulated data were upgraded for extrapolative prediction of energy indices by introducing an innovative model, which is the synergy of deflated and inflated prediction factors. The innovative model yielded a trendy prediction data for energy consumption, gross domestic product, carbon dioxide emission and human development index. However, the oil price was untrendy, which could be attributed to odd circumstances. Moreover, the sensitivity of the differential rate terms was instrumental in discovering the overwhelming effect of independent indices on the dependent index. Clearly, this paper has accomplished interpolative and extrapolative prediction of energy indices and equally recommends for further investigation of the untrendy nature of oil price.

关键词： energy indices differential model normalization simulation inflation deflation predictive factor and prediction rate

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On the Use of Second and Third Moments for the Comparison of Linear Gaussian and Simple Bilinear White Noise Processes

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Open Journal of Statistics 2018年第3期8卷 562-583页

作者： Christopher Onyema Arimie Iheanyi Sylvester Iwueze maxwell azubuike ijomah Elechi Onyemachi Department of Mathematics and Statistics University of Portharcourt Portharcourt Nigeria Department of Statistics Federal University of Technology Owerri Nigeria

The linear Gaussian white noise process (LGWNP) is an independent and identically distributed (iid) sequence with zero mean and finite variance with distribution . Some processes, such as the simple bilinear white noise process (SBWNP), have the same covariance structure like the LGWNP. How can these two processes be distinguished and/or compared? If is a realization of the SBWNP. This paper studies in detail the covariance structure of . It is shown from this study that;1) the covariance structure of is non-normal with distribution equivalent to the linear ARMA(2, 1) model;2) the covariance structure of is iid;3) the variance of can be used for comparison of SBWNP and LGWNP.

关键词： White Noise Process Normality Stationarity Invertibility Covariance Structure

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